ArticleInternational journal for numerical methods in biomedical engineering2012
Geometric modeling of subcellular structures, organelles, and multiprotein complexes.
Article in International journal for numerical methods in biomedical engineering, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Automated segmentation of soft X-ray tomography: Native cellular structure with submicron resolution at high-throughput for whole-cell quantitative imaging in yeast.Molecular biology of the cell · 2025Article
- Multiscale differential geometry learning of networks with applications to single-cell RNA sequencing data.Computers in biology and medicine · 2024Article
- The de Rham-Hodge Analysis and Modeling of Biomolecules.Bulletin of mathematical biology · 2020Article
- A review of mathematical representations of biomolecular data.Physical chemistry chemical physics : PCCP · 2020Review
- MathDL: mathematical deep learning for D3R Grand Challenge 4.Journal of computer-aided molecular design · 2020Article
- DG-GL: Differential geometry-based geometric learning of molecular datasets.International journal for numerical methods in biomedical engineering · 2019Article
- Representability of algebraic topology for biomolecules in machine learning based scoring and virtual screening.PLoS computational biology · 2018Article
- Sequence-based multiscale modeling for high-throughput chromosome conformation capture (Hi-C) data analysis.PloS one · 2018Article
- TopologyNet: Topology based deep convolutional and multi-task neural networks for biomolecular property predictions.PLoS computational biology · 2017Article
- Fast Simulation of Lipid Vesicle Deformation Using Spherical Harmonic Approximation.Communications in computational physics · 2017Article
- Multidimensional persistence in biomolecular data.Journal of computational chemistry · 2015Article
- Persistent homology analysis of protein structure, flexibility, and folding.International journal for numerical methods in biomedical engineering · 2014Article
- New software developments for quality mesh generation and optimization from biomedical imaging data.Computer methods and programs in biomedicine · 2014Article
- Multiscale geometric modeling of macromolecules I: Cartesian representation.Journal of computational physics · 2014Article
- Multiscale geometric modeling of macromolecules II: Lagrangian representation.Journal of computational chemistry · 2013Article
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Authors and funding
4 authors.
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Abstract
Recently, the structure, function, stability, and dynamics of subcellular structures, organelles, and multiprotein complexes have emerged as a leading interest in structural biology. Geometric modeling not only provides visualizations of shapes for large biomolecular complexes but also fills the gap between structural information and theoretical modeling, and enables the understanding of function, stability, and dynamics. This paper introduces a suite of computational tools for volumetric data processing, information extraction, surface mesh rendering, geometric measurement, and curvature estimation of biomolecular complexes. Particular emphasis is given to the modeling of cryo-electron microscopy data. Lagrangian-triangle meshes are employed for the surface presentation. On the basis of this representation, algorithms are developed for surface area and surface-enclosed volume calculation, and curvature estimation. Methods for volumetric meshing have also been presented. Because the technological development in computer science and mathematics has led to multiple choices at each stage of the geometric modeling, we discuss the rationales in the design and selection of various algorithms. Analytical models are designed to test the computational accuracy and convergence of proposed algorithms. Finally, we select a set of six cryo-electron microscopy data representing typical subcellular complexes to demonstrate the efficacy of the proposed algorithms in handling biomolecular surfaces and explore their capability of geometric characterization of binding targets. This paper offers a comprehensive protocol for the geometric modeling of subcellular structures, organelles, and multiprotein complexes.
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